MoveFlux gives you software, data analytics, artificial intelligence, and related services. Together, we apply these to give networkers at your events what they want.
This results in direct and indirect financial benefits for you.
Time is valuable and irreplaceable.
Networking seems deceptively simple. However, folks concurrently weigh time, economics, and the value of their existing connections when networking.
Barack Obama goes to a “small” hundred person event at the Yale Club near Grand Central. Mr. Obama has thirty minutes to spare and wants to meet the three most interesting people in the room. Other men and women in the room share--perhaps to a lesser degree--Mr. Obama’s time constraint. They have time to meet no more than the six most interesting people in the room.
Mathematically, there are 5,050 possible combinations for one-on-one, eight-to-ten-minute networking conversations possible, even at this “small” hundred-person (plus one ex-president) event. Go to a thousand-person conference and watch this number jump to 499,500.
People also seek economic value--immediate, short, or long-term--directly or indirectly from a networking connection. This holds whether people are job hunting, raising capital, hiring, or investing. Again, the better the matching on this dimension, the better the networking outcomes.
Folks also calculate the direct social value of their relationships. The quality, quantity, and value of introductions people make indirectly impact their reputations and revenues. People on both sides of the introduction judge whether it’s worth it both for them and their connections.
Matcher is seeded with algorithms and statistical models made from various types of free and purchased data.
Politics is part of many people’s identities and hence it’s a key variable in figuring out networking matches. In February 2018, ~28% of the population identified themselves as Republicans. ~27% were Democrats and ~42% identified as unaffiliated to a party. Furthermore, the Libertarian segment is 94% white and 68% male. Insights inferred from these and other data points were fed into our process.
We also gave a three-minute survey to people from our extensive and varied network. Questions spanned behaviors indicating introversion, tendency to conform, and what specifically the networkers are looking for. Then we applied our proprietary statistical models and machine learning techniques to enhance the insights. We mixed these in with Google’s multibillion-dollar, and hundred-plus man-year artificial intelligence platform and interfaces to come up with our turbo-charged matching engine.
We customize and tweak our survey product for your customer base. Then we perform segmentation analytics on your database. After that we apply our algorithms and models to provide the three best matches for each person for your networking event. We recommend eight to ten minutes of guided conversations for each match. (MoveFlux’s Coach product is a conversation-based interface that can help with both the logical and emotional aspects of these short but focused conversations).
Afterwards, people rate their matches. In the context of ratings, people also flag inappropriate behavior. Then our artificial intelligence can make adjustments on future matches and filters.
Matcher tries to balance the two types of errors. A) A False positive -- A match with a wrong person, B) A False negative -- Eliminating a match with a really right person. The balance and the cutoff decisions vary based on overall customer or prospect segment and the specific characteristics of your data.